Text Classification
Transformers
PyTorch
English
distilbert
fill-mask
legal
PyTorch
sentiment-analysis
text-embeddings-inference
Instructions to use ajinathgh/sentiment_analysis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ajinathgh/sentiment_analysis with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ajinathgh/sentiment_analysis")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("ajinathgh/sentiment_analysis") model = AutoModelForMaskedLM.from_pretrained("ajinathgh/sentiment_analysis") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 78ed1918266fdd34f258d065dd9bd0d56bfd9c201b9a49e0474364f32536407f
- Size of remote file:
- 268 MB
- SHA256:
- 30cbde1037aa466a8d8d722a8648582ee1ea26a23a41cc127ffc4df39d0bc930
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